Since cardiovascular disease is the most common cause of death in the Western countries, there is a strong need to diagnose and to quantify cardiac diseases early enough. The cardiac imaging techniques have improved considerably during the last years providing nowadays detailed anatomic and functional information on the heart. In addition, the automated analysis of the cardiac images has also been intensively developed.
Segmentation of cardiac images is a prerequisite for obtaining many cardiac indices, such as left ventricular volume and ejection fraction. Several approaches have been proposed for the automated segmentation of the ventricles and/or myocardium from magnetic resonance (MR) images. Cine datasets contain images normally from 10-30 cardiac phases and produce therefore detailed information on the cardiac function during the cycle. Tagged MR images provide a golden standard for the cardiac motion analysis, as the tags visible in the images are tracked. However, the analysis of cardiac function in clinical practice is still often based on standard MR images and visual inspection. Although segmentation tools developed for cardiac segmentation could basically be applied to each time instant separately, the techniques based on deformable models provide a natural framework for tracking the motion and changes in chamber volumes within the cine datasets.
MR imaging generates a stack of slice images from user defined locations. The typical pixel size of an MR slice is about 1 mm×1 mm. However, the pixel in the MR image is three-dimensional, i.e. each slice, as well as pixel, has also thickness indicating the region from which it is acquired. In other words, the gray-value of each pixel is an average from all tissues inside a box, such as 1 mm×1 mm×5 mm if the slice thickness is 5 mm. Due to signal-to-noise ratio, the slice thickness is typically higher than the pixel size. The problem in increasing the slice thickness is that the images become smoother and small spatial details are lost.
Typically, several MR image series are acquired during one imaging session. If a subject moves during the imaging session, the relation between image series, derived from the image headers, is lost and image registration is needed to realign the images. A subject may move because of several reasons, e.g. coughing, breathing or change of inconvenient pose. Breathing is a major source of movement artifacts in cardiac imaging, as the heart's own movement is handled by the ECG gating. Studies about the movements of the heart due to respiration can be found from related art. When the cine sequences are used to track the cardiac motion, an image series produced during a breath hold contains typically slices from several time points but only from one spatial location. If the phase of the breathing cycle is not similar during all acquisitions, slices from different image series will be misaligned relative to each other, and a volume built from the image series does not represent the real anatomy of the subject.
The tracking of the heart has usually concentrated only on ventricles and/or epicardium using short-axis images. Because the slice thickness is much higher than the pixel size in slice level, the tracking of the basal and apical regions of the ventricles using short-axis images is difficult. In practice, the ventricles are usually simply cutted by a plane at some basal level. Therefore, the use of two or more imaging directions is considered meaningful to improve the accuracy of image analysis
One method is disclosed in publication WO 01/75483A1, wherein two MR image stacks, acquired preferably orthogonally, are fused in order to improve the image contrast and resolution. At first, the stacks are registered with each other and a simple registration method based on translation of image stacks by maximizing the correlation between the image gradients is proposed. A high-resolution three dimension volume (image stack with low slice thickness) is produced by fusing the registered stacks. In the publication a back-projection technique is used to create the volume. The objective of the publication is to provide a method for improving the contrast and resolution of the images, and that is done by fusing the stacks and generating one high-resolution data set.
What is needed then is an improved solution for acquiring quantitative information of the heart. Such a solution should take into a account drawbacks of related art, e.g. blurring effect of the images. This invention addresses such a need.